Superconductors have zero resistivity below their critical temperatures, enabling them to carry large amounts of current. Therefore, superconductors can be used to construct powerful electrical machines with light and compact designs. However, one key difficulty when designing superconducting machines is that superconductors dissipate heat when they carry AC current or in AC magnetic fields. This heat dissipation (AC loss) in a low temperature environment adds to the cost and difficulties of keeping the superconductors at low operational temperature. The AC loss reduces system efficiency because up to a hundred times the cooling power in room temperature is required to remove it. In order to increase the machine efficiency it is therefore vital to be able to accurately estimate how much AC loss is dissipated in a superconducting machine and to identify strategies to reduce this loss. Significant progress has been made towards understanding the AC loss of superconductors in research laboratories worldwide. However, estimating the AC loss of superconductors in electrical machines is an intrinsically difficult task. There is a complicated interaction between the current and the magnetic field inside an electrical machine and the influence of this interaction on the machine AC loss is unknown at this moment. Actions, both experimentally and numerically, are required to understand the AC loss of superconducting machines. The aim of this project is to develop new experimental and numerical tools to estimate the AC loss of superconducting machines. We will design an experiment to measure the AC loss of superconductors in a simulated electrical machine environment. We will also develop a new FEM model, which will be validated by experimental data, to efficiently estimate the AC loss of fully superconducting machines. Furthermore, we will use the model to identify new strategies to reduce the AC loss and improve the efficiency of fully superconducting machines, based on the latest HTS technologies.
|Effective start/end date||1/12/16 → 7/05/18|
- Engineering and Physical Sciences Research Council