The porous electrode coating (PEC) plays a key role in lithium-ion battery cells (LIB). Recent advancements in electrochemical-mechanical coupled (EMC) simulations of active particles in LIBs have elucidated the complex interdependencies between mechanical stress and lithium concentration [1]. However, EMC simulations at a cell level are often hindered by the lack of a proper macro-scale homogenized mechanical model for the PEC-layer. In anodes, the active particles have a heterogeneous morphology, are elasto-plastic, and are held together by polymer binders, resulting in a complicated micro-scale mechanical behaviour. The goal of our research is to reveal the macro-scale bulk elastic properties of an anode PEC-layer during battery operations. In a micro-scale particle-resolved FEM simulation, a box of meshed particles undergoes a uni-axial strain compression. The resulting stress-strain relationship of the box can be extracted as the macro-scale bulk behaviour. In [2], this method is used to investigate a cathode PEC-layer during calendering. In this study, we extend this method to non-spherical particles to obtain an improved macro-scale homogenized mechanical model of an anode PEC-layer. In our micro-scale simulations, the binder phase is modelled by the contact interaction between particles. Uni-axial strain compressions of the box with various particle geometries, mechanical particle properties, and contact coefficients are simulated under loading conditions typical for battery cells during operation. The most important result of this study is to characterize the macro-scale lateral bulk behaviour of an anode PEC-layer. This is challenging due to its small thickness (<100 µm), yet it is essential for deriving the constitutive equation of a macro-scale homogenized mechanical model of a PEC-layer. In conclusion, micro-scale particle-resolved FEM simulations can serve as a pivotal tool in LIB development, particularly as they complement direct measurements by enabling the analysis of material behaviour under scenarios that may otherwise be cost-inefficient to assess.