State-dependent transient model switching for electrode drying: Multiscale coupling to a multizone dryer process model

Reducing energy use for the electrode drying process, which accounts for more than 38% of the total energy use in battery manufacturing, is crucial for a sustainable battery industry. However, systematic optimization of the drying process has been limited because the governing transport mechanisms evolve as solvent is removed, and conventional approaches lack an integrated treatment of these distinct stages. This study presents a novel state-dependent, dual-physics switching approach for multistage electrode-drying optimization to address the limitations of conventional methods that treat stages in isolation despite evolving transport mechanisms. At the electrode scale, the formulation employs criterion-based transient switching between models, ensuring consistent treatment of regime changes throughout the process. We develop a multiscale simulation that couples the transient electrode-scale analysis with a steady dryer process model. Using this coupled framework, we perform Bayesian optimization to identify multizone set-points that minimize energy use while satisfying the outlet moisture-content specification. Under identical throughput, the proposed method reduced total energy use by 56.4% without compromising product quality. This integrated multiscale framework can be adapted to other electrode products by incorporating their material properties, enabling material-specific efficiency improvements. • Novel dual-physics model-switching approach proposed for electrode drying. • Integrated micro–macro simulation of moisture transport in multichamber ovens. • Optimized drying profiles reduced energy consumption by 56.4%. • Framework adaptable for material-specific electrode manufacturing strategies. • Proposed approach supports sustainable, energy-efficient battery production practices.