Thermal Energy Storage (TES) devices, which leverage the constant-temperature thermal capacity of the latent heat of a Phase Change Material (PCM), provide benefits to a variety of thermal management systems by decoupling the absorption and rejection of thermal energy. Control-oriented models are needed to predict the behavior of the TES to maximize the capabilities and efficiency of the overall system and experimental validation is needed to demonstration the validity of the simplifying assumptions used to produce these control- oriented models. This thesis experimentally demonstrates the predictive capabilities of a switched Moving Boundary (MB) model that captures the key dynamics of the TES with significantly fewer states as compared to traditional approaches. A graph-based modeling approach is used to model the heat flow through the TES and the moving boundary captures the time-varying liquid and solid regions of the TES. A Finite State Machine (FSM) is used to switch between four different modes of operation based on the State-of-Charge (SOC) of the TES. The switched MB approach is shown to have similar accuracy and lower computational cost compared to traditional modeling approaches when predicting the SOC of an experimental TES device.