Abstract: The purpose of this work is to optimize a Switched Reluctance Motor (SRM) for an automotive application, specifically for a fully electric car. A new optimization approach is proposed. This unique approach transforms automotive customer requirements into an optimization problem, based on sound knowledge of a SRM theory. The approach combines an analytical and a finite element analysis of the motor to quantify static nonlinear and dynamic performance parameters, as phase currents and motor torque maps, an output power and power losses in order to find the optimal motor as close to the reality as possible, within reasonable time. The new approach yields the optimal motor which is competitive with other types of already proposed motors for automotive applications. This distinctive approach can also be used to optimize other types of electrical motors, when parts specifically related to the SRM are adjusted accordingly.
Abstract: This paper deals with a novel approach of power
transformers diagnostics. This approach identifies the exact location
and the range of a fault in the transformer and helps to reduce
operation costs related to handling of the faulty transformer, its
disassembly and repair. The advantage of the approach is a
possibility to simulate healthy transformer and also all faults, which
can occur in transformer during its operation without its
disassembling, which is very expensive in practice. The approach is
based on creating frequency dependent impedance of the transformer
by sweep frequency response analysis measurements and by 3D FE
parametrical modeling of the fault in the transformer. The parameters
of the 3D FE model are the position and the range of the axial short
circuit. Then, by comparing the frequency dependent impedances of
the parametrical models with the measured ones, the location and the
range of the fault is identified. The approach was tested on a real
transformer and showed high coincidence between the real fault and
the simulated one.