Online Parameter Adaptation for the Dynamical Model of a Tri-electrode Zinc-Air Flow Cell

The paper explores the modeling, prediction, and monitoring of a tri-electrode zinc-air flow cell, contributing to the Battery Management System solutions for zinc-based storage systems. It focuses on airflow batteries, known for their promising safety and robustness features yet exhibiting significant performance variability and parameter fluctuations over cycles and lifespan. Building upon earlier work on modeling and parameter identification at constant current discharge rates and investigations into dynamic behavior changes at varying discharge currents, this study proposes an online parameter adaptation approach based on the structural properties of the dynamical model. This approach uses operational data to mitigate parameter discrepancies arising from zinc reaction chemistry while addressing capacity and current-voltage non-linearities induced by cell stress from specific discharge profiles.