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The purpose of this paper is to introduce a reverted way to design electrical machines. The authors present a work flow that systematically yields electrical machine geometries from given air gap fields.

The solution process exploits the inverse Cauchy problem. The desired air gap field is inserted to this as the Cauchy data, and the solution process is stabilized with the aid of linear algebra.

The results are verified by solving backwards the air gap fields in the standard way. They match well with the air gap fields inserted as an input to the system.

The paper reverts the standard design work flow of electrical motor by solving directly for a geometry that yields the desired air gap field. In addition, a stabilization strategy for the underlying Cauchy problem is introduced.

The authors aim to search for a practical and accurate way to get good loss estimates for coil filaments in electrical machines, for example transformers. At the moment including loss estimations into standard finite element computations is prohibitively expensive for large coils.

A low-dimensional function space for finite element method (FEM) is introduced on the filament-air interface and then extended into the filament to significantly reduce the number of unknowns per filament. Careful choice of these extensions enables good loss estimate accuracy. The result is a system matrix assembly block that can be used verbatim for all filaments, further reducing the cost. Both net current and voltage per length of the filament are readily available in the problem formulation.

The loss estimates from the developed model agree well with traditional FEM and the computation times are faster.

To produce accurate loss estimates in large coils, the low-dimensional function space is constricted on the filament boundaries. The proposed method enables electrical engineers to compute the ohmic losses of individual conductors.