Data-driven electrode processing cost optimization for lithium-ion battery production

Abstract Lithium-ion batteries (LIBs) are central to the global transition toward decarbonization, powering electric vehicles and grid-scale storage. Yet, reducing production costs remains a critical challenge as industries scale to meet projected demands exceeding 6 TWh by 2030. This study examines the cost sensitivity of mixing, coating, and drying steps, which together account for over 20% of overall production costs and are among the most defect-prone in electrode fabrication. Existing techno-economic models often treat these steps in aggregate, obscuring the impact of specific parameter variations. Using the process-based ProZell cost model and a Plackett–Burman design of experiments, we show that optimizing key parameters can reduce costs by up to $22 million annually (~2.0%) in a 10 GWh lithium iron phosphate (LFP) cylindrical cell facility. Cathode mixing time was the most influential variable, with an 80% reduction corresponding to ~ $12 million in savings (~1.12%). Increasing anode and cathode coating speeds by 80% yields ~ $8.8 million in combined savings. Emerging innovations, including dry electrode and high-shear mixing, offer additional savings. BatPaC modeling identified cathode thickness limits of 310.3 µm (LFP) and 168.8 µm (nickel manganese cobalt), beyond which optimization is constrained. These findings offer actionable insights for scalable, chemistry-specific cost reductions in LIB manufacturing.