Two low-order, parametric Magnetic Contact Switch models are developed for the forces and moments that a rotating propeller undergoes in forward flight.The models are derived using a first-principles-based approach, and are computationally efficient in the sense of being represented by explicit expressions.The parameters for the models can be identified either using supervised learning/grey-box fitting from labelled data, or can be predicted using only the static load coefficients (i.e.
, the hover thrust and torque coefficients).The second model is a multinomial model that is derived by means of a Taylor series expansion of the first model, and can be viewed as a lower-order lumped parameter model.The models and parameter generation methods are experimentally tested against 19 propellers tested in a wind Vacuum Swivel Adaptor tunnel under oblique flow conditions, for which the data is made available.The models are tested against 181 additional propellers from existing datasets.