  In order to achieve a better understanding of degradation processes in
lithium-ion batteries, the modelling of cell dynamics at the mircometer scale
is an important focus of current mathematical research. These models lead to
large-dimensional, highly nonlinear finite volume discretizations which, due to
their complexity, cannot be solved at cell scale on current hardware. Model
order reduction strategies are therefore necessary to reduce the computational
complexity while retaining the features of the model. The application of such
strategies to specialized high performance solvers asks for new software
designs allowing flexible control of the solvers by the reduction algorithms.
In this contribution we discuss the reduction of microscale battery models with
the reduced basis method and report on our new software approach on integrating
the model order reduction software pyMOR with third-party solvers. Finally, we
present numerical results for the reduction of a 3D microscale battery model
with porous electrode geometry.
