Predicting the thermal state of generators on-board UAVs

On future Unmanned Air Vehicles (UAVs) it is envisaged that the power requirements of all on-board electrical systems will increase. Whilst, in most flight (mission) situations the installed generation capacity will have adequate capacity to operate the systems, it is possible that during certain abnormal situations the generators on-board may be forced to operate under very high load conditions. The main failure mechanism for a generator is overheating and subsequent disintegration of windings, hence the research problem being addressed here is that of modelling the thermal dynamics of a generator in such a way that the model can be used to predict future temperatures given knowledge of the future mission requirements. The temperature predictions will be used to allow prioritising of the mission actions in order to allow maximum utilisation of power generation capacity without overheating. This paper presents research undertaken to model the thermal state of a generator, applying a model type usually used in electrical machine design as part of a condition monitoring system. The research implementing a state update algorithm based on a Kalman filter to allow predictions to be made from any start point during flight is also presented. Experimental results from a lab scale test-rig show that for a 6hr varying load test the model maintains an accuracy of ±2°C except for certain short periods, with errors being caused by large variations in the load. Also shown is that the effective prediction horizon does not appear to be limited over time. Instead, it is found to be dependent on when significant changes in load occur.