This paper deals with rotor position estimation of switched reluctance motors (SRM). The estimation method can be applied in SRM sensorless control of position speed and torque controllers. The implementation suggested is based on a real time adaptive filter. The measured variables are supply voltage and stator currents. These currents are used repeatedly for rotor position estimation by using linear adaptive filter which time constant is adjusted to the speed of the rotor. The result of this estimation is a rather precise and convenient rotor angle determining device for SRM sensorless control electrical drives.
The purpose of the paper is to point out an approach that ensures a mathematical description of different Switched Reluctance Motors (SRM) with central geometrical symmetry of active poles, such as SRM6-4, SRM8-6, SRM12-8 etc. The SRM becomes popular nowadays because of the rapid development of control electronics and simulation facilities. In order to build up a proper SRM drive, it is necessary to create convenient simulation model of the motor. But the identification of this motor is rather sophisticated due to the fact that the stator inductance depends on both, position of the rotor and the stator current. This fact extremely complicates the mathematical model of the SRM, describing it by partial differential equations. To make the things easier, neural network descriptions are suggested. They simplify the process of identification using Matlab Simulink. These descriptions also reflect the high nonlinearity of the magnetic circuit and the influence of the air gap.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.