Learning curves for solid oxide fuel cells

In this article we present learning curves for solid oxide fuel cells (SOFCs). With data from fuel cell manufacturers we derive a detailed breakdown of their production costs. We develop a bottom-up model that allows for determining overall SOFC manufacturing costs with their respective cost components, among which material, energy, labor and capital charges. The results obtained from our model prove to deviate by at most 13% from total cost figures quoted in the literature. For the R&D stage of development and diffusion, we find local learning rates between 13% and 17% and we demonstrate that the corresponding cost reductions result essentially from learning-by-searching effects. When considering periods in time that focus on the pilot and early commercial production stages, we find regional learning rates of 27% and 1%, respectively, which we assume derive mainly from genuine learning phenomena. These figures turnout significantly higher, approximately 44% and 12% respectively, if also effects of economies-of-scale and automation are included. When combining all production stages we obtain lr = 35%, which represents a mix of cost reduction phenomena. This high learning rate value and the potential to scale up production suggest that continued efforts in the development of SOFC manufacturing processes, as well as deployment and use of SOFCs, may lead to substantial further cost reductions.

► We present learning curves for fuel cells based on empirical data.
► We disentangle different cost reduction mechanisms for SOFCs.
► We distinguish between learning-by-doing, R&D, economies-of-scale and automation.