Increasing efficiency of the switched reluctance generator using parametric regression and optimization methods

Abstract

In this paper the switched reluctance generator (SRG) is explored considering the improvement of its efficiency. This machine generates a DC power that is directly related to input driving parameters. Simulation results are presented bringing a case study of parametric regression to track the best efficiency for any input parameters: excitation voltage and turn off angle. A method known as parametric regression is applied along with deterministic optimization in order to find an equation that provides the driving parameters so the machine can generate DC power associated to high efficiency.