In this presentation, we consider a real-valued two dimensional discrete time intermittent Kalman filtering problem over an erasure channel with an energy harvesting transmitter. The cost of transmitting an observation is one unit of energy and side information about the erasure state of the channel may or may not be available at the transmitting sensor. The transmitter uses energy management by leveraging the available energy storage and side information. Building upon our recent work for a scalar dynamical system, we consider different cases for the structure of the state evolution matrix A and we study the threshold for the growth rate of the two-dimensional state dynamics for bounded asymptotic expected state estimation error covariance.