Cryogenic Lumped-Parameter Thermal Network for Superconducting Electrical Machine Design

Although the electromagnetic performance of superconducting machines has received considerable attention, their thermal analysis remains largely unaddressed. In particular, there is no consensus on the feasible operating temperature of superconducting armature windings, even though this is a critical design parameter. To address this problem, this paper proposes a cryogenic lumped-parameter thermal network (LPTN) to quantify the temperature drop between the superconducting armature and the cryogenic coolant. As a case study, the model is used to analyze and improve the conceptual design of a 2.5 MW cryo-electric aviation motor. For the liquid hydrogen–cooled design, it is found that the armature temperature can not be reduced below 34 K without compromising the machine performance. This is further increased to 40 K when gaseous helium is used as a coolant. Moreover, heat leaks through the thermal insulation was found to double the temperature rise of the armature windings. These findings emphasize that detailed thermal constraints must be considered in the design of superconducting machines and to predict their achievable performance.