Abstract
Accurate monitoring of battery aging is pivotal for optimizing the performance of zinc-air batteries (ZABs). To obtain precise information about battery aging, an appropriate definition of state-of-health (SOH) is essential. However, the definition of SOH for ZABs has not been well-defined. This work introduces a novel SOH concept based on energy efficiency and integrates it with an underlying linear parameter varying (LPV) model. Crucially, the LPV model is chosen for its capability to represent nonlinear behavior, making it apt for capturing the intricacies of battery aging dynamics. With SOH defined as the scheduling parameter, electrochemical impedance spectroscopy (EIS) is employed to assess the influence of SOH. The results validate the model's robustness, as its predictions align closely with the empirical data. This newly proposed SOH definition exhibits a strong association with the model parameters. Furthermore, the efficacy of the LPV technique, especially when paired with the proposed SOH, suggests significant potential for refining battery aging monitoring in ZABs.
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