An NSGA-III-based Method for Identifying Carbon Hotspots in the Rolling Process of Lithium-Ion Battery Electrodes

To address the complexity and difficulty in precisely tracing carbon emissions during the rolling process of lithium-ion battery electrodes, this paper proposes an NSGA-III-based method for identifying carbon hotspots in this process. The method establishes a multi-objective optimization model that correlates key process parameters, such as rolling pressure, speed, and temperature, with objectives including carbon emission intensity, energy consumption efficiency, and production cost. It constructs objective functions aimed at minimizing carbon emissions and optimizing rolling quality. By leveraging NSGAIII’s strong global search capability and mechanism for maintaining population diversity, the method efficiently obtains the Pareto optimal solution set. Experimental results demonstrate that this approach can accurately locate hotspot areas in the rolling process where carbon emissions account for over $40 \%$ of the total. It also proposes a collaborative optimization scheme for process parameters, achieving a reduction in carbon emissions per unit product while ensuring electrode quality, thereby providing a quantifiable path for enterprise process optimization.