Second-life lithium batteries, State of Charge, Nonlinear observer, Battery model
Abstract
Batteries in electric vehicles (EVs) are replaced when they reach about 80% of their nominal capacity. Avoiding disposal and utilizing the remaining potential in these batteries is the main motivation behind second-life battery (B2U) research applications. The state of charge (SOC), although a parameter that informs the system about the energy available in the batteries for use, cannot be directly measured by sensors. It is the responsibility of the battery management system (BMS) to have an algorithm to estimate it with the necessary precision. Thus, this work addresses the development and tuning of a nonlinear observer to estimate the SOC of second-life batteries. The tuning method uses the linearized model of the observer and the root locus, aiming to reduce the convergence time of the observation error. In addition to the simplicity of the tuning method, simulation results show that convergence occurs more rapidly, and in all analyzed cases, estimation errors were less than 2.5%.
