A co-estimation framework for state of charge and parameters of Lithium-ion battery with robustness to aging and usage conditions

Aging and usage conditions affect the battery parameters, such as capacity and changes in the opencircuit voltage (OCV) and internal resistance dependencies on the state of charge (SOC). This article proposes an onboard strategy for the simultaneous estimation of these parameters and their robust evaluation during the battery life. The proposed co-estimation framework consists of a set of interconnected subsystems grounded on the integration of recursive least-squares techniques and a Luenberger-like observer which are independently designed by relying on moving averages of voltage and current measurements. Each subsystem is separately activated through logic variables, which select the operating conditions proper for the estimation purposes and allows tracking of model parameters variations. The effectiveness of the solution is shown over experiments with a cylindrical LG M50 T INR21700 Li-ion cell with NMC cathode and graphite/silicon anode.