Signed Distance Function-Based Analytical Modeling of Electric Machine Geometry

Signed distance functions (SDFs) may be employed for parametric-based optimization of electric machines (EMs). The objective of this paper is to present a method for constructing an SDF-based analytical representation of complex EM geometries. This is achieved by transforming the SDF of simple geometric primitives into complex geometries through function composition. These composite functions can then be used to model material properties over the domain of an EM. A permanent magnet synchronous motor is used as a case study.