ABSTRACT
This chapter explores the identification of synchronous machine parameters from noise-corrupted measurements. It shows how the time-domain maximum likelihood technique can be used to remove the effect of noise from estimated parameters. The chapter explains a systematic procedure for induction motor modelling. Modeling the dynamical properties of a system is an important step in analysis and design of control systems. Modeling often results in a parametric model of the system that contains several unknown parameters. The nonlinear nature of switched reluctance machine (SRM) and high saturation of phase winding during operation makes the modeling of SRM a challenging work. SRMs have undergone rapid development in hybrid electric vehicles and other automotive applications. Electric machines are widely used in electric/hybrid vehicles. Identifying appropriate model structures of these machines and estimating the parameters of the models has become an important part of the automotive control design.
